File size: 4,874 Bytes
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license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: V10-distilbert-text-classification-model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# V10-distilbert-text-classification-model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2088
- Accuracy: 0.9546
- F1: 0.8213
- Precision: 0.8192
- Recall: 0.8243
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.5687 | 0.11 | 50 | 2.1779 | 0.1200 | 0.0687 | 0.0913 | 0.0550 |
| 1.1872 | 0.22 | 100 | 1.1610 | 0.6475 | 0.4010 | 0.4470 | 0.3901 |
| 0.6574 | 0.33 | 150 | 0.9675 | 0.6300 | 0.3389 | 0.4603 | 0.3683 |
| 0.548 | 0.44 | 200 | 0.6524 | 0.8165 | 0.5001 | 0.4898 | 0.5117 |
| 0.3506 | 0.55 | 250 | 0.6884 | 0.7985 | 0.5037 | 0.6467 | 0.5073 |
| 0.3233 | 0.66 | 300 | 0.5294 | 0.8553 | 0.5177 | 0.5012 | 0.5353 |
| 0.3211 | 0.76 | 350 | 0.5028 | 0.8553 | 0.5989 | 0.5974 | 0.6058 |
| 0.2611 | 0.87 | 400 | 0.7703 | 0.8387 | 0.6148 | 0.5917 | 0.6521 |
| 0.3259 | 0.98 | 450 | 0.6041 | 0.8335 | 0.6121 | 0.5925 | 0.6442 |
| 0.2196 | 1.09 | 500 | 0.5109 | 0.8737 | 0.6300 | 0.6026 | 0.6665 |
| 0.1712 | 1.2 | 550 | 0.6030 | 0.8488 | 0.6231 | 0.7507 | 0.6528 |
| 0.175 | 1.31 | 600 | 0.5176 | 0.8783 | 0.6549 | 0.7620 | 0.6752 |
| 0.257 | 1.42 | 650 | 0.3901 | 0.8873 | 0.6462 | 0.7626 | 0.6783 |
| 0.1759 | 1.53 | 700 | 0.4053 | 0.8955 | 0.6774 | 0.7709 | 0.6947 |
| 0.1309 | 1.64 | 750 | 0.3624 | 0.9251 | 0.7857 | 0.7883 | 0.7927 |
| 0.2394 | 1.75 | 800 | 0.3332 | 0.9171 | 0.7749 | 0.7751 | 0.7848 |
| 0.165 | 1.86 | 850 | 0.6878 | 0.8510 | 0.6446 | 0.6970 | 0.6394 |
| 0.1421 | 1.97 | 900 | 0.3987 | 0.8718 | 0.6345 | 0.7590 | 0.6170 |
| 0.1361 | 2.07 | 950 | 0.3393 | 0.9253 | 0.7738 | 0.7734 | 0.7872 |
| 0.1292 | 2.18 | 1000 | 0.3194 | 0.9300 | 0.8017 | 0.8128 | 0.7930 |
| 0.0754 | 2.29 | 1050 | 0.3485 | 0.9245 | 0.7871 | 0.7842 | 0.8006 |
| 0.1345 | 2.4 | 1100 | 0.2564 | 0.9387 | 0.8022 | 0.7974 | 0.8104 |
| 0.0593 | 2.51 | 1150 | 0.2132 | 0.9541 | 0.8159 | 0.8222 | 0.8109 |
| 0.1019 | 2.62 | 1200 | 0.2234 | 0.9472 | 0.8070 | 0.8044 | 0.8127 |
| 0.0735 | 2.73 | 1250 | 0.2183 | 0.9535 | 0.8155 | 0.8250 | 0.8072 |
| 0.113 | 2.84 | 1300 | 0.2716 | 0.9128 | 0.7208 | 0.8006 | 0.7118 |
| 0.0838 | 2.95 | 1350 | 0.2957 | 0.9330 | 0.7999 | 0.7929 | 0.8128 |
| 0.0797 | 3.06 | 1400 | 0.2758 | 0.9437 | 0.8075 | 0.8117 | 0.8058 |
| 0.0612 | 3.17 | 1450 | 0.2450 | 0.9139 | 0.7200 | 0.7983 | 0.7140 |
| 0.0492 | 3.28 | 1500 | 0.2501 | 0.9480 | 0.8089 | 0.8089 | 0.8118 |
| 0.0294 | 3.38 | 1550 | 0.2745 | 0.9374 | 0.8035 | 0.8011 | 0.8084 |
| 0.0248 | 3.49 | 1600 | 0.2561 | 0.9434 | 0.8099 | 0.8073 | 0.8144 |
| 0.0621 | 3.6 | 1650 | 0.2312 | 0.9491 | 0.8135 | 0.8190 | 0.8094 |
| 0.0541 | 3.71 | 1700 | 0.2512 | 0.9472 | 0.8140 | 0.8177 | 0.8119 |
| 0.0509 | 3.82 | 1750 | 0.2195 | 0.9516 | 0.8145 | 0.8173 | 0.8125 |
| 0.0452 | 3.93 | 1800 | 0.2418 | 0.9480 | 0.8140 | 0.8175 | 0.8120 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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